Episode 26: Random Learning on the Short

In this episode, I kept it short and sweet with a new statistical journal reference, data science job scraping, and random learning for R-packages. References: Generalized resilience and robust statistics Stochastic continuum-armed bandits with additive models: Minimax regrets and adaptive algorithm Generate random ID values for subjects in SAS Linear Regression Equation Explained An Example of Specifying Within-Subjects Factors in Repeated Measures Designing Online Data Science Training for the Modern Age Optimizing my search for Data scientist jobs by scraping Indeed with R Seeking Inspiration from Random Learning R-packages: BiOFI: Feature Identification Between Metabolome and Microbiome in Disease and Health glmmrBase: Specification of Generalised Linear Mixed Models REDCapTidieR: Extract 'REDCap' Databases into Tidy 'Tibble's verbaliseR: Make your Text Mighty Fine betaSandwich: Robust Confidence Intervals for Standardized Regression Coefficients DynForest: Random Forest with Multivariate Longitudinal Predictors roBTT: Robust Bayesian T-Test alqrfe: Adaptive Lasso Quantile Regression with Fixed Effects recurrentpseudo: Creates Pseudo-Observations and Analysis for Recurrent Event Data alkahest: Pre-Processing XY Data from Experimental Methods